Method and Rfid Reader for Evaluating a Data Stream Signal in Respect of Data and/or Collison

ABSTRACT

A method for evaluating, by an radio frequency identification reader ( 1 ), a data stream signal (DS) in respect of data and/or collision, comprises comparing the data stream signal (DS) with at least one threshold level, particularly a data bit level and/or a collision level, and evaluating the results of the comparison, wherein both the threshold level and its adaptation speed (α(n)) are adapted in dependence of the course of the data stream signal (DS) and/or the course of said threshold level.

FIELD OF THE INVENTION

The invention relates to a method for evaluating by a radio frequencyidentification reader a data stream signal in respect of data and/orcollision, comprising comparing the data stream signal with at least onethreshold level, particularly a data bit level and/or a collision level,and evaluating the results of the comparison.

The invention further relates to a radio frequency identification readerbeing configured to evaluate a data stream signal in respect of dataand/or collision, by comparing the data stream signal with at least onethreshold level, particularly a data bit level and/or a collision level,and evaluating the results of the comparison.

The invention further relates to a computer program product directlyloadable into the memory of a programmable radio frequencyidentification reader, comprising software code portions for performingthe steps of a method according to the first paragraph when said productis run on the radio frequency identification reader.

BACKGROUND OF THE INVENTION

In known Radio Frequency IDentification (RFID) systems fixed thresholdlevels are used for detecting data and collisions in data stream signalsreceived by an RFID reader. In this context, the term “fixed thresholdlevels” means that said threshold levels are either set in advance orare selected as a predefined multiple of an input noise signal.

However, these known RFID systems have shown the disadvantage that incase of varying signal levels the threshold levels used for thedetection of data and collisions cannot be adapted, which may result indetection errors. Varying signal levels may for instance arise fromsignal beat or from varying coupling between the antennas of an RFIDreader and RFID tags, respectively.

From the document U.S. Pat. No. 5,300,922 a periodic pulsediscrimination system for use with electronic article surveillancessystems is known which is capable of detecting valid tag pulses whilediscriminating against periodic pulses caused by resonances andinterfering carriers as well as random noise. Circuitry that determinesthe periodicity of a pulse signal and is responsive to amplitudedifferences between successive detected pulses controls an adaptivethreshold and sampling window to discriminate against signals having anincorrect periodicity and an inadequate envelope rise time. Thisdocument generally discusses topics in respect of adaptive detection ofperiodic signals and noise, but does not disclose processes or means fordetecting data and collisions in data stream signals among the signalsof multiple RFID tags by use of adaptive threshold levels.

OBJECT AND SUMMARY OF THE INVENTION

It is an object of the invention to provide a method of the type definedin the opening paragraph and a device of the type defined in the secondparagraph, in which the disadvantages defined above are avoided.

In order to achieve the object defined above, with a method according tothe invention characteristic features are provided so that a methodaccording to the invention can be characterized in the way definedbelow, that is:

A method for evaluating by an radio frequency identification reader adata stream signal in respect of data and/or collision, comprisingcomparing the data stream signal with at least one threshold level,particularly a data bit level and/or a collision level, and evaluatingthe results of the comparison, wherein both the threshold level and itsadaptation speed are adapted in dependence of the course of the datastream signal and/or the course of said threshold level.

In order to achieve the object defined above, with an RFID readeraccording to the invention characteristic features are provided so thatthe RFID reader carries out the steps of the method according to thepresent invention.

In order to achieve the object defined above, with a computer programproduct according to the invention characteristic features are providedso that a computer program product according to the invention isdirectly loadable into the memory of a programmable RFID reader, whereinthe computer program product comprises software code portions forperforming the steps of a method according to the invention when saidproduct is run on the RFID reader.

In order to achieve the object defined above, an RFID reader accordingto the invention comprises an arithmetic-logic unit and a memory andprocesses the computer program product according to the above paragraph.

The characteristic features according to the invention provide asubstantial improvement of the detection rate and speed of data andcollisions in data stream signals of RFID readers. The present inventionis of particular advantage for RFID systems that are operated inenvironments and/or under such conditions wherein the signal levels maychange over time. This may be due to antenna detuning, noise or changesof the magnetic coupling between RFID reader and RFID tags.

The measures as claimed in claim 2 provide the advantage that with anappropriately set basic adaptation speed a fast initial adaptation ofthe threshold levels can be achieved. The basic adaptation speed may bevaried over time, thus enabling learning modes. This may be done using alearning curve.

The measures as claimed in claim 3 or claim 4, respectively, provide theadvantage that the threshold levels can be adapted faster if samples ofthe data stream signal have a high variance, or can be frozen if thevariance is too high.

The measures as claimed in claim 5 provide the advantage that anadaptation of bit level to collisions or outliers is prevented. Further,quick adaptation of the threshold levels to steps can be achieved.

The measures as claimed in claim 6 provide the advantage that adaptationof the threshold levels is selectively activated or deactivated. Forexample a “1” bit level should not try to adapt to “0” sample values.Further, adaptation can be prevented when the distance of an actualsample value of the data stream signal to the threshold level is toohigh.

The measures as claimed in claim 7 provide the advantage thatinterferences can be handled that cause increased signal levels in caseof signal collision.

The measures as claimed in claim 8 provide the advantage that a quickdecision can be made whether in case of signal collision the data can berecovered or not.

It should further be noted that the features of the inventive method canbe directly implemented in the RFID reader.

The aspects defined above and further aspects of the invention areapparent from the exemplary embodiment to be described hereinafter andare explained with reference to this exemplary embodiment.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in more detail hereinafter withreference to an exemplary embodiment. However, the invention is notlimited to this exemplary embodiment.

FIG. 1 shows a schematic block circuit diagram of an RFID system.

FIG. 2 shows a schematic block circuit diagram of an RFID tag.

FIG. 3 shows a signal diagram explaining strong signal collision.

FIG. 4 shows a signal diagram explaining weak signal collision.

FIG. 5 to FIG. 8 show exemplary diagrams of various adaptive thresholdlevels defined according to the present invention.

FIG. 9 shows a diagram of the amplitude of samples of a data streamsignal and adaptive bit levels and collision levels.

FIG. 10 shows a block circuit diagram of an implementation of thepresent invention.

DESCRIPTION OF EMBODIMENTS

FIG. 1 shows a schematic block circuit diagram of an RFID (RadioFrequency Identification) system comprising an RFID reader 1 and anumber of RFID tags 2 a, 2 b, wherein, for the sake of clearness, onlytwo RFID tags 2 a and 2 b are depicted. RFID reader 1 communicates withthe RFID tags 2 a, 2 b in a contact-less manner via modulatedelectromagnetic signals, provided the RFID tags 2 a, 2 b are within thetransmission and receiving range of the RFID reader 1. The RFID reader 1comprises control means 3, like a microprocessor or micro-controller,which control means 3 communicate via a data bus with program storagemeans 4. The program storage means 4 is adapted to store an operatingsystem OS for basic operation of the control means 3 and applicationprogram code SW to be processed by the control means 3. The programstorage means 4 may be configured as a non-volatile memory, like a PROM,EPROM, EEPROM or the like, wherein in the present case a ROM utilized.The program storage means 4 may also be configured as a user definableASIC, PAL or the like. Further, the control means 3 and the programstorage means 4 may be integrated into a single chip. It should beobserved that the application program code SW and the operating systemOS may be integrated. The control means 3 further communicate with arandom access memory 5. The control means 3, when processing the programcode SW, cooperate with input/output means 8, which e.g. can beconfigured as a link interface to a computer.

The RFID reader 1 further comprises an antenna 7 for transmittingelectromagnetic signals SS to the RFID tags 2 a, 2 b. Theseelectromagnetic signals SS may be used for both transmitting data to theRFID tags 2 a, 2 b and energizing the RFID tags 2 a, 2 b if they areconfigured as passive tags. The RFID tags 2 a, 2 b respond to the RFIDreader with response signals RS1, RS2. Data exchange between the RFIDreader 1 and the RFID tags 2 a, 2 b may be accomplished by standard datatransmission protocols and standard modulation methods. For instance,the electromagnetic signal SS sent from the RFID reader 1 to the RFIDtags 2 a, 2 b is a pulse position coded modulated signal according tothe international standard ISO15693 but also other transmission methodsmay be considered. The response signals RS1, RS2 from the RFID tags 2 a,2 b to the RFID reader are e.g. load modulated signals, wherein acarrier signal or sub carrier signal contained in the electromagneticsignal SS is modulated by switching a load impedance connected to theantennas of the RFID tags 2 a, 2 b, so that varying energy is drawn fromthe carrier signal or sub-carrier signal. Switching the load impedancesat the RFID tags causes a change of the impedance of the antenna 7 ofthe RFID reader 1 and hence a varying amplitude of the voltage at theantenna 7 of the RFID reader 1, which varying voltage amplituderepresents an input signal IS. For recovery of data contained in theinput signal IS the input signal IS is rectified or demodulated,respectively, yielding data stream signal DS. The RFID reader 1 extractsthe data coded in the data stream signal DS by comparing it with definedbit levels. In order to reduce the errors in extracting the datacollision levels can be defined additionally and used for comparison, aswill be explained in detail below.

FIG. 2 shows a schematic block circuit diagram of an exemplaryembodiment of the RFID tags 2 a, 2 b. It should be observed that theconfiguration of the RFID tags 2 a, 2 b is not part of the presentinvention, but is explained only for a comprehensive understanding ofthe present invention. Each RFID tag 2 a, 2 b is configured as a passivetag and comprises an antenna 10, an analogue radio frequency interface11 that is connected to the antenna 10, a digital control unit 12 thatis connected to the analogue radio frequency interface 11, and a memory13 that is connected to the digital control unit 12. The memory 13 is anon-volatile memory, like an EEPROM, so that data that are written intothe memory 13 during communication with the RFID reader 1 remain storedeven when the RFID tag 2 a, 2 b is switched off, e.g. because it leavesthe transmitting range of the RFID reader 1 and is therefore not longerenergized by the RFID reader 1. Memory 13 may also contain program codefor operating the digital control unit 12 and a unique identificationnumber. Antenna 10 receives the electromagnetic signals SS from the RFIDreader 1 and passes them to the analogue radio frequency interface 11.In general, the analogue radio frequency interface 11 comprises arectifier REG and a voltage regulator VREG with integrated energystorage element, like a capacitor, to derive from the receivedelectromagnetic signals SS the necessary operating voltage VDD for thedigital control unit 12 and the memory 13. Further, analogue radiofrequency interface 11 comprises a demodulator DEMOD to extract data DINfrom the electromagnetic signals SS and to pass them to the digitalcontrol unit 12. Digital control unit 12 processes the received data DINand may respond to the RFID reader 1 by creating output data DOUT andpassing them to the analogue radio frequency interface 11. Analogueradio frequency interface 11 comprises a modulator MOD that modulatesthe output data DOUT and transmits the modulated signals as responsesignals RS1, RS2 via antenna 10.

For a successful communication between the RFID reader 1 and the RFIDtags 2 a, 2 b it is necessary to frequently carry out synchronizationbetween said devices. Further, in frequent time intervals the RFIDreader searches for RFID tags being present in its receiving range bysending out broadcast inventory commands, requesting all RFID tags toconfirm their presence by returning their identification numbers. Thisinventory process may result in signal collisions at the antenna 7 ofthe RFID reader, when more than one RFID tag respond at the same time,as will now be explained with reference to the diagrams of FIGS. 3 and4.

The diagram depicted in FIG. 3 shows in the upper two lines responsesignals RS1, RS2 transmitted at the same time by RFID tags 2 a, 2 b. Theresponse signals RS1, RS2 contain the bit streams “1-1” (RS1) and “1-0”(RS2) in Manchester coding. Manchester coding is a form of datacommunications line coding in which each bit of data is signified by atleast one transition. Each bit is transmitted over a predefined timeperiod. Superposition of the response signal RS1, RS2 creates the inputsignal IS at the antenna of the RFID reader 1 as is depicted in thelowest line of the diagram, which input signal IS is demodulated to datastream signal DS. Regarding input signal IS or data stream signal DS,respectively, it will be appreciated that the first bit still contains atransition, although the signal amplitude has been increased to abouttwice the signal amplitude of signals RS1, RS2. However, when comparingdata stream signal DS with appropriately set bit levels the RFID reader1 is still able to correctly recover the correct bit values “1” andassign them to response signals RS1, RS2. In contrast thereto, thesecond bits of signals RS1, RS2 superimpose to a signal form in theinput signal IS and the demodulated data stream signal DS, respectively,that has no transition, which is a violation of Manchester coding. Thislacking transition constitutes a so-called “strong” collision, since theRFID reader is unable to recover the data bits.

The diagram of FIG. 4 shows response signals RS1 and RS2 from RFID tags2 a, 2 b as received by the RFID reader. It will be appreciated that theresponse signals RS1, RS2 appear with different amplitudes at the RFIDreader (for instance due to different distances from the RFID reader 1)resulting in an input signal IS and a demodulated data stream signal DS,respectively, as depicted in the lowest line of the diagram. Althoughsuperimposing of response signals RS1, RS2 at antenna 7 of the RFIDreader 1 causes a signal collision in the data stream signal DS, in thiscase the collision is only a “weak” one, since the data stream signal DSstill shows a signal transition that allows for the correct recovery ofthe data (“1” for signal RS1, “0” for RS2) provided that the data streamsignal DS is compared with appropriately set bit levels.

In order to improve the data detection rate and speed and to reduce theerror rate the present invention proposes to use adaptive thresholdlevels for comparison with the data stream signal DS. Such adaptivethreshold levels are useful whenever the values that represent thethreshold level change over time. This may be due to antenna detuning,noise or changes of the magnetic coupling (eg. moving vicinityintegrated circuit cards (VICC)). In order to achieve best results thepresent invention further proposes to adapt the threshold levels with anadaptive adaptation speed, as will be explained herein below.

In an embodiment of the present invention adaptation of the thresholdlevels is based on exponential smoothing. It's adaptation speed α (α,α_(var): 0 . . . 1εR) is a function of the variance (L_(var)), therelative distance of the new sample to the level

$\left( \frac{{this} - {L\left( {n - 1} \right)}}{L\left( {n - 1} \right)} \right),$

an external value (α₀) and an on/off variable (ε{0,1}). The term thisdenotes the actual sample x(n) of the data stream signal DS. The factorsF control the weight of each part.

The variance is estimated by the following equations. These equationsare basically the same as for the adaptive level itself.

$\begin{matrix}{{\alpha_{var}(n)} = \left\lbrack {{\left( {{\alpha_{0,{var}}(n)} + {\frac{{{this} - {L\left( {n - 1} \right)}}}{L\left( {n - 1} \right)} \cdot F_{\Delta,{var}}}} \right) \cdot {on}}\text{/}{{off}(n)}} \right\rbrack_{0}^{1}} & \left\lbrack {{EQ}\mspace{14mu} 1} \right\rbrack \\{{L_{var}(n)} = \left\lceil {{{L_{var}\left( {n - 1} \right)} \cdot \left( {1 - {\alpha_{var}(n)}} \right)} + {{{{this} - {L\left( {n - 1} \right)}}} \cdot {\alpha_{var}(n)}}} \right\rceil^{L_{{var},\max}}} & \left\lbrack {{EQ}\mspace{14mu} 2} \right\rbrack\end{matrix}$

The maximum variance L_(var,max) prevents divergence effects forpositive F_(Δ,var) (more variance

faster level adaptation

higher misplacement for the next sample

more variance

. . . ) if set properly.

The main level is calculated as follows:

$\begin{matrix}{{\alpha (n)} = \left\lbrack {{\left( {{\alpha_{0}(n)} + {\frac{{{this} - {L\left( {n - 1} \right)}}}{L\left( {n - 1} \right)} \cdot F_{\Delta}} + {\frac{L_{var}(n)}{L\left( {n - 1} \right)} \cdot F_{var}}} \right) \cdot {on}}\text{/}{{off}(n)}} \right\rbrack_{0}^{1}} & \left\lbrack {{EQ}\mspace{14mu} 3} \right\rbrack \\{{L(n)} = {{{L\left( {n - 1} \right)} \cdot \left( {1 - {\alpha (n)}} \right)} + {{this} \cdot {\alpha (n)}}}} & \left\lbrack {{EQ}\mspace{14mu} 4} \right\rbrack\end{matrix}$

The adaptation speed is controlled by various parameters. The followingtable lists these parameters including a short explanation.

Parameter Explanation α (n) Basic adaptation speed. This parameter maybe varied over time, thus enabling learning modes. This may be doneusing a learning curve. If α₀ is chosen negative, it forces a slowdownof adaptation.

Variance dependence of the level. This maybe used to letthe level adaptfaster if input samples have a high varianceor to freeze the level ifthe variance is too high.

Distance dependence of level to new value. This preventsthe level fromadapting to collisions or outliers. It may alsobe used to quickly adaptthe level to steps. on/off(n) This constant ∈ {0, 1} may be used toactivate or deactivate the adaptation. For example a “1”-level shouldnot try to adapt to zeros. The constant may also be controlled by|this-L(n − 1)|/L(n − 1). This prevents adaptation in any case if thedistance to the level is too high. F The F-parameters (factors) controlthe weight of the parts mentioned in this table. The higher the F-value(e.g. FΔ), the more dominant the corresponding part will get. Thisparameters may also be chosen variable, changing the behavior of theadaptive level over time.

Next, applications of the present invention are explained by way ofexamples.

Example 1

In order to discriminate bits “1” and bits “0” in an input signal thatis received by the RFID reader from RFID tags a bit threshold level forbit “1” (denoted L_(“1”)) and a bit threshold level for bit “0” (denotedL_(“0”)) is defined. It is further defined:

$\begin{matrix}{{{center}\mspace{11mu} (n)} = {{{center}\mspace{11mu} {\left( {n - 1} \right) \cdot \left( {1 - \alpha_{center}} \right)}} + {\frac{{L_{``1"}(n)} + {L_{``0"}(n)}}{2} \cdot \alpha_{center}}}} & \left\lbrack {{EQ}\mspace{14mu} 5} \right\rbrack \\{{{on}\text{/}{{off}_{``1"}(n)}} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} {this}} > {{center}\left( {n - 1} \right)}} \\0 & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 6} \right\rbrack \\{{{on}\text{/}{{off}_{``0"}(n)}} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} {this}} < {{center}\left( {n - 1} \right)}} \\0 & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 7} \right\rbrack\end{matrix}$

The above threshold levels are shown for a sample x in the diagram ofFIG. 5. The bit decision is defined by:

$\begin{matrix}{{{Bit}\mspace{11mu} (n)} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} {this}} > {{center}(n)}} \\0 & {{{if}\mspace{14mu} {this}} < {{center}(n)}} \\{undefined} & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 8} \right\rbrack\end{matrix}$

Example 2

In order to enhance the evaluation of the data stream signal DS in sucha way that not only bits “1” and “0” can be discriminated, but alsocollisions may be found, two collision levels L_(coll,“1”)(n) andL_(coll,“0”)(n), i.e. one for each bit level, are defined according tothe following equations:

L _(coll,“1”)(n)=L _(“1”)(n)−L _(var,“1”)(n)·F _(coll,“1”)  [EQ 9]

L _(coll,“0”)(n)=L _(“0”)(n)+L _(var,“0”)(n)·F _(coll,“0”)  [EQ 10]

The above threshold levels are shown for a sample x in the diagram ofFIG. 6. The occurrence of collisions is decided according to thefollowing equation:

$\begin{matrix}{{{Collision}\mspace{11mu} (n)} = \left\{ \begin{matrix}{true} & {{{if}\mspace{14mu} {L_{{coll}.{``0"}}(n)}} \leq {this} \leq {L_{{coll}.{``1"}}(n)}} \\{false} & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 11} \right\rbrack\end{matrix}$

Example 3

It should be noted that interferences may create increased instead ofdecreased levels in case of collisions. In order to cope with thisproblem, two additional collision threshold levels have to beintroduced, resulting in four collision threshold levels:

L _(coll,“1”,u)(n)=L _(“1”)(n)+L _(var,“1”)(n)·F _(coll,“1”)  [EQ 12]

L _(coll,“1”,l)(n)=L _(“1”)(n)−L _(var,“1”)(n)·F _(coll,“0”)  [EQ 13]

L _(coll,“0”,u)(n)=L _(“0”)(n)+L _(var,“0”)(n)·F _(coll,“0”)  [EQ 14]

L _(coll,“0”,l)(n)=L _(“0”)(n)−L _(var,“0”)(n)·F _(coll,“0”)  [EQ 15]

The above threshold levels are shown for a sample x in the diagram ofFIG. 7. The occurrence of collisions is decided according to thefollowing equation:

$\begin{matrix}{{{Collision}\mspace{11mu} (n)} = \left\{ \begin{matrix}{true} & {{{if}\mspace{14mu} {this}} \leq {L_{{{coll}.{``0"}}{.1}}(n)}} \\{true} & {{{if}\mspace{14mu} {L_{{coll}.{``0"}.u}(n)}} \leq {this} \leq {L_{{{coll}.{``1"}}{.1}}(n)}} \\{true} & {{{if}\mspace{14mu} {this}} \geq {L_{{coll}.{``1"}.u}(n)}} \\{false} & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 16} \right\rbrack\end{matrix}$

Example 4

Using two different collision levels per bit level allows the system todiscriminate “weak” from “strong” collisions:

L _(coll,“1”,strong)(n)=L _(“1”)(n)−L _(var,“1”)(n)·F_(coll,“1”,strong)  [EQ 17]

L _(coll,“1”,weak)(n)=L _(“1”)(n)−L _(var,“1”)(n)*F_(coll,“1”,weak)  [EQ 18]

L _(coll,“0”,strong)(n)=L _(“0”)(n)+L _(var,“0”)(n)·F_(coll,“0”,strong)  [EQ 19]

L _(coll,“0”,weak)(n)=L_(“0”)(n)+L _(var,“0”)(n)·F _(coll,“0”,weak)  [EQ20]

The above threshold levels are shown for a sample x in the diagram ofFIG. 8. The occurrence of strong and weak collisions is decidedaccording to the following equation:

$\begin{matrix}{{{Strong}\mspace{14mu} {Collision}\mspace{11mu} (n)} = \left\{ \begin{matrix}{true} & \begin{matrix}{{{{if}\mspace{14mu} {L_{{coll}.{``0"}.{strong}}(n)}} \leq {this} \leq}} \\{L_{{coll}.{``1"}.{strong}}(n)}\end{matrix} \\{false} & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 21} \right\rbrack \\{{{Weak}\mspace{14mu} {Collision}\mspace{11mu} (n)} = \left\{ \begin{matrix}{true} & \begin{matrix}{{{if}\mspace{14mu} {L_{{coll}.{``0"}.{weak}}(n)}} \leq} \\{{this} < {L_{{coll}.{``0"}.{strong}}(n)}}\end{matrix} \\{true} & \begin{matrix}{{{if}\mspace{14mu} {L_{{coll}.{``1"}.{strong}}(n)}} <} \\{{this} \leq {L_{{coll}.{``1"}.{weak}}(n)}}\end{matrix} \\{false} & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 22} \right\rbrack\end{matrix}$

with F_(coll,“1”,strong)>F_(coll,“1”,weak) andF_(coll,“0”,strong)>F_(coll,“0”,weak). Combining examples 3 and 4, i.e.defining two collision levels per bit level and weak/strong collisionlevels, eight collision levels are obtained.

Example 5

FIG. 9 shows a diagram of the amplitude of samples of a data streamsignal DS and adaptive bit levels and collision levels. This example isan implementation of above equations [EQ 1] to [EQ 11], with equations[EQ 6] and [EQ 7] respectively, having been substituted by the followingequations:

$\begin{matrix}{{{on}\text{/}{{off}_{``1"}(n)}} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} {this}} > {L_{{coll}.{``1"}}\left( {n - 1} \right)}} \\0 & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 23} \right\rbrack \\{{{on}\text{/}{{off}_{``0"}(n)}} = \left\{ \begin{matrix}1 & {{{if}\mspace{14mu} {this}} < {L_{{coll}.{``0"}}\left( {n - 1} \right)}} \\0 & {otherwise}\end{matrix} \right.} & \left\lbrack {{EQ}\mspace{14mu} 24} \right\rbrack\end{matrix}$

The diagram of FIG. 9 is explained by the following table:

DS Sample No. Explanation 0-5 Very fast adaptation controlled by α₀ inlearning mode. α₀ decreases along a cosine rolloff learning pattern.Please note that the “1”-level (positive) will not react to zeros(negative) and vice versa.  6-30 Only ones with increasing variance.“0”-level is fixed while “1”-level changes at most samples. However,collisions (samples below “1”- collisionlevel) are ignored. 31-38Collisions for both levels. All levels are fixed to their previousstate. 39-55 Zeros with decreasing level but increasing variance (eg.VICC is moving out of the field).

FIG. 10 shows a block circuit diagram of an implementation of thepresent invention. It should be observed that this implementation may beembedded in form of hardware implementation (level adaptation means LAas part of control means 3 of RFID reader 1, see FIG. 1) or softwareimplementation, wherein the software is stored in the program storagemeans 4 or loadable into the program storage means 4 and/or the memory 5of the RFID reader 1. In many situations a computer program product thatcomprises software code portions for performing the steps of the methodaccording to the invention is already pre-stored in such an RFID reader,e.g. in a ROM or EPROM or any other permanent memory. It may also bethat the computer program product can be fed into the RFID reader by theaid of a data carrier on which the computer program product is stored.

In the block circuit diagram of FIG. 10 the following associationsbetween blocks and equations are given:

“1” level: [EQ 3], [EQ 4]

“0” level: [EQ 3], [EQ 4]

“1” var level: [EQ 1], [EQ 2]

“0” var level: [EQ 1], [EQ 2]

center level: [EQ 5]

right part: [EQ 17] to [EQ 20]

comparator: [EQ 5], [EQ 21] to [EQ 24]

It can be mentioned that so called RFID systems are systems used forgoods or animal identification. But also so called near fieldcommunication devices (NFC devices) can be considered. In general ideaof this invention can always be applied for communication systems, inwhich systems a bit stream and collision detection is required. Itallows to make decisions on signals, for which signals the variance ofthe level (e.g. caused by noise) is a problem during operation.

It should be noted that the above-mentioned embodiments illustraterather than limit the invention, and that those skilled in the art willbe able to design many alternative embodiments without departing fromthe scope of the appended claims. In the claims, any reference signsplaced between parentheses shall not be construed as limiting the claim.The word “comprising” does not exclude the presence of elements or stepsother than those listed in a claim. The word “a” or “an” preceding anelement does not exclude the presence of a plurality of such elements.The invention may be implemented by means of hardware comprising severaldistinct elements, and/or by means of a suitably programmed processor.In the device claim enumerating several means, several of these meansmay be embodied by one and the same item of hardware. The mere fact thatcertain measures are recited in mutually different dependent claims doesnot indicate that a combination of these measures cannot be used toadvantage.

1. A method for evaluating by an radio frequency identification reader adata stream signal in respect of data and/or collision, comprisingcomparing the data stream signal with at least one threshold level,particularly a data bit level and/or a collision level, and evaluatingthe results of the comparison, wherein both the threshold level and itsadaptation speed are adapted in dependence of the course of the datastream signal and/or the course of said threshold level.
 2. A method asclaimed in claim 1, wherein a basic adaptation speed is set, whereinpreferably the basic adaptation speed is variable over time,particularly according to predefined learning curves.
 3. A method asclaimed in claim 1, wherein the adaptation speed is adapted independence of the variance of the threshold level.
 4. A method asclaimed in claim 3, wherein the variance dependence of the adaptationspeed is calculated by a nonlinear function.
 5. A method as claimed inclaim 1, wherein the adaptation speed is adapted in dependence of thedistance of the threshold level to an actual sample value of the datastream signal.
 6. A method as claimed in claim 1, wherein the adaptationof the threshold level is activated/deactivated in dependence of anactual sample value of the data stream signal or in dependence of thedistance of the threshold level to an actual sample value of the datastream signal.
 7. A method as claimed in claim 1, wherein for each bitlevel an upper and a lower collision level is defined.
 8. A method asclaimed in claim 1, wherein the threshold levels comprise “strong”collision levels defining collisions where no data recovery is possibleand “weak” collision levels defining collisions where data recovery isstill possible.
 9. An radio frequency identification reader beingconfigured to evaluate a data stream signal in respect of data and/orcollision, by comparing the data stream signal with at least onethreshold level, particularly a data bit level and/or a collision level,and evaluating the results of the comparison, wherein the radiofrequency identification reader is configured to carry out the steps ofthe method according to claim
 1. 10. An radio frequency identificationreader according to claim 9 comprising control means with anarithmetic-logic unit and a memory, wherein the radio frequencyidentification reader is adapted to process a computer program product.11. A computer program product being directly loadable into the memoryof a programmable radio frequency identification reader, comprisingsoftware code portions for performing the steps of a method according toclaim 1 when said product is run on the radio frequency identificationreader.
 12. A computer program product as claimed in claim 11, whereinthe computer program product is stored on a computer readable medium.